Various forms of imaging apparatus have been used extensively for medical applications. For example, fluoroscope systems, X-ray imaging systems, ultrasound imaging systems, computed tomography (CT) imaging systems, and magnetic resonance (MR) imaging (MRI) systems have been used for a number of years. Any number of medical examination, interventional procedures, diagnosis, and/or treatment may be provided using an appropriate one of the foregoing systems suited for the task.
Ultrasound imaging systems have been used as a tool for assisting interventional clinical procedures. For example, conventional two-dimensional (2D) ultrasound imaging has been used in the field of regional anesthesia to provide a way of “seeing” and tracking the delivery of the anesthetic with a needle, rather than attempting to achieve such a goal blindly using nerve stimulation technology. However, such 2D imaging brings with it many issues associated with training and ease-of-use. Anesthesiologists who are new to ultrasound imaging often relatively rapidly acquire the skill required for interpreting the location and orientation of the 2D plane presented in a conventional 2D image. However, it is significantly more difficult for the anesthesiologist to master the hand-eye coordination required to obtain both the target anatomy (e.g., nerve) and the interventional apparatus (e.g., needle) in the same 2D image, while trying to guide the interventional apparatus towards the target. Even more problematic, it is often difficult for the anesthesiologist to control the 2D image such that the interventional apparatus is meaningfully presented or shown in the 2D image.
A major reason for the hand-eye coordination problem in image-guided (e.g., ultrasound image-guided) interventional procedures is the fact that a 2D image is essentially a thin slice of a 3D space in which the observer is working within. Coordinating both hands for providing continuous alignment between a 3D object in space (e.g., a needle) and a relatively thin 2D slice (the image plane), while maintaining the anatomy of interest (e.g., nerve) within the image plane by observing the image displayed in the imaging device is understandably a very difficult task. These problems are not limited to the foregoing anesthesiologist example, but are present with respect to many interventional procedures, such as biopsies, line placements, catheter placements, etc.
Computing technology, having progressed dramatically in the last few decades, has provided three-dimensional (3D) (e.g., a data set providing information in an X, Y, and Z axes space) and even four-dimensional (4D) (e.g., a 3D image having a time axis added thereto) imaging capabilities. Although such 3D and 4D imaging technology arose from disciplines such as drafting, modeling, and even gaming, the technology has been adopted in the medical field. For example, computed tomography has been utilized with respect to X-ray images to produce 3D images. Furthermore, computerized 3D rendering algorithms have been utilized to enhance the visualization of 3D datasets from various imaging modalities including CT, MR, ultrasound etc.
The use of such computing technology to provide 3D and 4D images in the medical field has carried with it several disadvantages from its origins. For example, providing bi-axial freedom of movement/rotation with respect to each of the X, Y, and Z axes (i.e., 6 degrees of freedom), as derived from the drafting and modeling roots of 3D imaging, has typically been provided with respect to medical imaging where 3D and 4D imaging is available. Such degrees of freedom can be used to allow 2D cross-section images through a 3D volume (e.g., multi-planar reconstruction (MPR) images) in any plane. Particular orientations, such as top, bottom, left, and right, are often less important in the virtual world than presenting a desired portion of the rendered image to a viewer. Accordingly, object image (e.g., volume rendered image) and cross-section image (e.g., MPR image) orientation freedom has been provided by 3D and 4D image computing technology. However, providing such freedom with respect to certain medical imaging tasks has further compounded the aforementioned hand-eye coordination problems with respect to interventional procedures. Moreover, users in the medical field, such as the aforementioned anesthesiologists who are new to ultrasound imaging, often find it difficult if not impossible to control such images to locate and/or present the interventional apparatus and/or target in a meaningful way.
Several attempts have been made to facilitate identification of interventional instruments in images and/or framing interventional instruments within images. For example, sensor configurations, such as magnetic sensors, light sensors, etc., have been implemented with respect to various interventional instruments and corresponding imaging tools in order to facilitate identification of interventional instruments in images. Additionally, apparatus, such as needle guides, have been added for use with respect to interventional instruments and imaging tools in order to place the interventional instrument within the generated images. Likewise, complex systems, such as gyroscopes, have been implemented with respect to imaging tools and/or interventional instruments in order to facilitate placing interventional instruments within images. The foregoing attempts, however, require structural modification to the interventional instruments and/or imaging tools. Such modifications are often quite complex and expensive, and in all cases limits the particular interventional instruments and/or imaging tools which are available to a user seeking to receive the benefit of such techniques.